Abstract
We propose a simple method for classifying images to increase the reliability of steganalysis techniques in digital images. RS Steganalysis Method(RSM), Sample Pair Method(SPM), and Least Square Method(LSM) are the most reliable steganalysis methods in the literature for LSB replacement steganography on digital images in spatial domain. These methods give highly accurate results on most of the images. However all these methods show very high embedding ratio when no data or very small amount of data is hidden in some images. We propose a simple method to identify images which give very accurate results and images which give highly inaccurate results. The novelty of our method is that it does not require any knowledge about the cover images. The image classification is done based on certain statistical properties of the image, which are invariant with embedding. Thus it helps the steganalyst in attaching a level of confidence to the estimation he makes.
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References
Goljan, M., Fridrich, J., Du, R.: Detecting lsb steganography in colour and grey-scale images. Magazine of IEEE Multimedia, Special Issue on Security (October-November 2001)
Wu, X., Dumitrescu, S., Wang, Z.: Detection of lsb steganography via sample pair analysis. IEEE Transactions on Signal Processing 51(7), 1995–2007 (2003)
Tang, Q., Lu, P., Luo, X., Shen, L.: An improved sample pairs method for detection of lsb embedding. In: Fridrich, J. (ed.) IH 2004. LNCS, vol. 3200, pp. 116–127. Springer, Heidelberg (2004)
Anderson, R.J., Petitcolas, F.A.P.: On the limits of steganography. IEEE Journal of Selected Areas in Communications (Special issue on copyright and privacy protection)Â 16 (1998)
Du, R., Fridrich, J., Meng, L.: Steganalysis of lsb encoding in colour images. In: Proceedings of IEEE International Conference on Multimedia and Expo. New York City, NY, July 30-August 2 (2000)
Tao, Z., Xijian, P.: Reliable detection of lsb steganography based on the difference image histogram. In: Proc. IEEE ICAAP, Part III, pp. 545–548 (2003)
Ker, A.D.: Improved detection of lsb steganography in greyscale images. In: Fridrich, J. (ed.) IH 2004. LNCS, vol. 3200, pp. 97–115. Springer, Heidelberg (2004)
Liu, B., Luo, X., Liu, F.: Improved rs method for detection of lsb steganography. In: Gervasi, O., Gavrilova, M.L., Kumar, V., Laganá, A., Lee, H.P., Mun, Y., Taniar, D., Tan, C.J.K. (eds.) ICCSA 2005. LNCS, vol. 3481, pp. 508–516. Springer, Heidelberg (2005)
Ker, A.: Derivation of error distribution in least squares steganalysis. IEEE Transactions on Information Security and Forensics 2, 140–148 (2007)
Fridrich, J., Soukal, D.: Matrix embedding for large payloads. IEEE Transactions on Information Security and Forensics 7, 12–17 (2008)
Yang, C., Luo, X., Hu, Z., Gao, S.: A secure lsb steganography system defeating sample pair analysis based on chaos system and dynamic compensation. In: ICACT 2006, pp. 1014–1019 (2006)
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Shreelekshmi, R., Wilscy, M., Veni Madhavan, C.E. (2010). Image Classification for More Reliable Steganalysis. In: Meghanathan, N., Boumerdassi, S., Chaki, N., Nagamalai, D. (eds) Recent Trends in Network Security and Applications. CNSA 2010. Communications in Computer and Information Science, vol 89. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14478-3_7
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DOI: https://doi.org/10.1007/978-3-642-14478-3_7
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